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Biomarker-Based Designs of Phase III Clinical Trials for Personalized Medicine

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Developments in Statistical Evaluation of Clinical Trials

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Abstract

Advances in biotechnology and genomics have accelerated development of molecularly targeted treatments and prognostic and predictive biomarkers, particularly, in oncology. This chapter provides an overview of various biomarker-based designs for phase III randomized clinical trials to evaluate clinical utility of a biomarker or biomarker-based treatment, including biomarker-strategy, enrichment, and randomize-all designs. We also provide a simulation comparison of the randomize-all designs in terms of their ability to assert treatment efficacy for the correct patient population. Complex adaptive designs with development and validation of predictive biomarkers are also discussed.

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References

  1. Bogaerts, J., Cardoso, F., Buyse, M., Braga, S., Loi, S., et al.: Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nature Clinical Practice Oncology 3(10), 540–551 (2006). doi:10.1038/ncponc0591

  2. Buyse, M., Michiels, S., Sargent, D.J., Grothey, A., Matheson, A., et al.: Integrating biomarkers in clinical trials. Expert Review of Molecular Diagnostics 11(2), 171–182 (2011). doi:10.1586/erm.10.120

  3. Chau, C.H., Rixe, O., McLeod, H., Figg, W.D.: Validation of analytic methods for biomarkers used in drug development. Clinical Cancer Research 14(19), 5967–5976 (2008). doi:10.1158/1078-0432.CCR-07-4535

  4. Cobo, M., Isla, D., Massuti, B., Montes, A., Sanchez, J.M., et al.: Customizing cisplatin based on quantitative excision repair cross-complementing 1 mRNA expression: a phase III trial in non-small-cell lung cancer. Journal of Clinical Oncology 25(19), 2747–2754 (2007). doi:10.1200/JCO.2006.09.7915

  5. Cree, I.A., Kurbacher, C.M., Lamont, A., Hindley, A.C., Love, S.: A prospective randomized controlled trial of tumour chemosensitivity assay directed chemotherapy versus physician’s choice in patients with recurrent platinum-resistant ovarian cancer. Anticancer Drugs 18(9), 1093–1101 (2007). doi:10.1097/CAD.0b013e3281de727e

  6. Freidlin, B., Simon, R.: Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients. Clinical Cancer Research 11(21), 7872–7878 (2005). doi:10.1158/1078-0432.CCR-05-0605

  7. Freidlin, B., McShane, L.M., Korn, E.L.: Randomized clinical trials with biomarkers: design issues. Journal of the National Cancer Insititute 102(3), 152–160 (2010). doi:10.1093/jnci/djp477

  8. Freidlin, B., Jiang, W., Simon, R.: The cross-validated adaptive signature design. Clinical Cancer Research 16(2), 691–698 (2010). doi:10.1158/1078-0432.CCR-09-1357

  9. Hoering, A., Leblanc, M., Crowley, J.J.: Randomized phase III clinical trial designs for targeted agents. Clinical Cancer Research 14(14), 4358–4367 (2008). doi:10.1158/1078-0432.CCR-08-0288

  10. Jiang, W., Freidlin, B., Simon, R.: Biomarker-adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effect. Journal of the National Cancer Insititute 99(13), 1036–1043 (2007). doi:10.1093/jnci/djm022

  11. Karapetis, C.S., Khambata-Ford, S., Jonker, D.J., O’Callaghan C.J., Tu D., et al.: K-ras mutations and benefit from cetuximab in advanced colorectal cancer. New England Journal of Medicine 359(17), 1757–1765 (2008). doi:10.1056/NEJMoa0804385.

  12. Maitournam, A., Simon, R.: On the efficiency of targeted clinical trials. Statistics in Medicine 24(3), 329–339 (2005). doi:10.1002/sim.1975

  13. Mandrekar, S.J., Sargent, D.J.: Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges. Journal of Clinical Oncology 27(24), 4027–4034 (2009). doi:10.1200/JCO.2009.22.3701

  14. Matsui, S., Simon, R., Qu, P., Shaughnessy, J.D. Jr, Barlogie, B., et al.: Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicine. Clinical Cancer Research 18(21), 6065–6073 (2012). doi:10.1158/1078-0432.CCR-12-1206

  15. National Institutes of Health: Sample Size Calculation for Randomized Clinical Trials. http://linus.nci.nih.gov/brb/samplesize/sdpap.html

  16. Pusztai, L., Hess, K.R.: Clinical trial design for microarray predictive marker discovery and assessment. Annals of Oncology 15(12), 1731–1737 (2004). doi:10.1093/annonc/mdh466

  17. Sargent, D.J., Conley, B.A., Allegra, C., Collette, L.: Clinical trial designs for predictive marker validation in cancer treatment trials. Journal of Clinical Oncology 23(9), 2020–2027 (2005). doi:10.1200/JCO.2005.01.112

  18. Simon, R., Maitournam A.: Evaluating the efficiency of targeted designs for randomized clinical trials. Clinical Cancer Research 10(20), 6759–6763 (2004). doi:10.1158/1078-0432.CCR-04-0496

  19. Simon, R., Wang, S.J.: Use of genomic signatures in therapeutics development in oncology and other diseases. Pharmacogenomics Journal 6(3), 166–173 (2006). doi:10.1038/sj.tpj.6500349

  20. Simon, R.: The use of genomics in clinical trial design. Clinical Cancer Research 14(19), 5984–5993 (2008). doi:10.1158/1078-0432.CCR-07-4531

  21. Simon, R., Paik, S., Hayes, D.F.: Use of archived specimens in evaluation of prognostic and predictive biomarkers. Journal of the National Cancer Insititute 101(21), 1446–1452 (2009). doi:10.1093/jnci/djp335

  22. Simon, R.: Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology. Personalized Medicine 7(1), 33–47 (2010). doi:10.2217/pme.09.49

  23. Simon, R.: Clinical trials for predictive medicine. Statistics in Medicine 31(25), 3031–3040 (2012) doi:10.1002/sim.5401

  24. Slamon, D.J., Leyland-Jones, B., Shak, S., Fuchs, H., Paton, V., et al.: Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. New England Journal of Medicine 344(11), 783–792 (2001). doi:10.1056/NEJM200103153441101

  25. Song, Y., Chi, G.Y.: A method for testing a prespecified subgroup in clinical trials. Statistics in Medicine 26(19), 3535–3549 (2007). doi:10.1002/sim.2825

  26. Spiessens, B., Debois, M.: Adjusted significance levels for subgroup analyses in clinical trials. Contemporary Clinical Trials 31(6), 647–656 (2010). doi:10.1016/j.cct.2010.08.011

  27. Tsiatis. A.A.: The asymptotic joint distribution of the efficient score test for the proportional hazards model calculated over time. Biometrika 68(1), 311–315 (1981). doi:10.1093/biomet/68.1.311

  28. Wang, S.J., O’Neill, R.T., Hung, H.M.: Approaches to evaluation of treatment effect in randomized clinical trials with genomic subset. Pharmaceutical Statistics 6(3), 227–244 (2007). doi:10.1002/pst.300

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Acknowledgements

This research was partly supported by a Grant-in-Aid for Scientific Research (24240042) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. The views expressed in this chapter are the result of independent work and do not necessarily represent the views of the Pharmaceuticals and Medical Devices Agency.

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Authors and Affiliations

  1. Department of Biostatistics, Graduate School of Medicine, Nagoya University, Showa-ku, Nagoya, Japan

    Shigeyuki Matsui

  2. Pharmaceuticals and Medical Devices Agency, Chiyoda-ku, Tokyo, Japan

    Takahiro Nonaka

  3. Department of Statistical Science, School of Multidisciplinary Sciences, The Graduate University for Advanced Studies, Tachikawa, Tokyo, Japan

    Yuki Choai

Authors
  1. Shigeyuki Matsui
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  2. Takahiro Nonaka
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  3. Yuki Choai
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Corresponding author

Correspondence to Shigeyuki Matsui .

Editor information

Editors and Affiliations

  1. Department of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands

    Kees van Montfort

  2. Behavioural Science Institute, University of Nijmegen, Nijmegen, The Netherlands

    Johan Oud

  3. Department of Hematology, Erasmus Medical Center, Rotterdam, The Netherlands

    Wendimagegn Ghidey

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Matsui, S., Nonaka, T., Choai, Y. (2014). Biomarker-Based Designs of Phase III Clinical Trials for Personalized Medicine. In: van Montfort, K., Oud, J., Ghidey, W. (eds) Developments in Statistical Evaluation of Clinical Trials. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55345-5_14

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